Schedule Risk Analysis (SRA) offers an essential methodology for integrating comprehensive risk assessment within the project scheduling process. Utilising the Monte Carlo Analysis, SRA not only simulates a wide array of potential outcomes but also provides a statistical range that enhances the understanding of potential delays and their implications on projects. It provides a more understanding of potential delays and their implications, enabling project managers to devise effective mitigation strategies. Through probabilistic analysis, SRA helps in forecasting the most realistic project timelines, considering the inherent uncertainties in any project.

Deep Dive into Schedule Risk Analysis

At the core of Schedule Risk Analysis is the Monte Carlo method, a sophisticated statistical technique that predicts the outcomes of uncertain events through random sampling and statistical modelling. In the context of SRA, this method simulates thousands of potential project scenarios, taking into account identified risks, to generate a comprehensive probability distribution of completion dates. This process reveals a wide spectrum of potential project outcomes, from the most optimistic scenarios to the most pessimistic ones.

Figure 1: Iterations run by risk tools like Primavera Risk Analysis

The Critical Role of Schedule Risk Analysis Workshops

Schedule Risk Analysis Workshops are fundamental to the SRA process. These workshops are collaborative sessions where project teams come together to identify time-related risks, subsequently linking these risks to specific schedule activities. A key outcome of these workshops is the development of three-point estimates for each identified risk, categorising them into optimistic, pessimistic, and most likely durations. Below is an example of Risk Register of Schedule Risk Workshop, in which time risks are identified and 3 points estimate are assigned for each.

Sl. No.	Discipline	Title: Description	Best case days	Most likely days	Worst case days
1	Commissioning	Due to design, construction and/or commissioning there is a risk that the finished quality will not be the performance specification	10	30	55
2	Commissioning	Defects during Commissioning	5	20	40
3	Construction	Due to excessive rain events, there is a risk of wet weather impacting construction activities	5	20	40
4	Design	Due to design approval iterations and comments on comments there is a risk of ongoing design rework	5	20	40
5	Construction	Due to construction techniques, there is a risk of leaking/cracking of water retaining structures	10	20	60
6	Construction	Due to inaccurate contaminated site, there is a risk of encountering unexpected hazardous materials during construction	5	10	20
7	Safety & Security	Due to construction activities, there is a risk of an Industrial Accident – Plant and Equipment Fire/Rollover	5	10	20
8	Commercial & Legal	Due to errors or omissions in information documents provided by external stakeholders	5	10	20
9	Safety & Security	Due to the emergence of new pandemic strains, there is a risk to labour productivity and safety	5	10	20

Figure 2: Schedule Risk Register – 3 Points Estimate

Navigating Through Probabilities: P50, P80, and P90

The metrics derived from Monte Carlo simulations, specifically P50, P80, and P90, are critical in assessing the project’s completion timelines and outcomes. They represent varying degrees of confidence in the project’s potential completion dates and play a pivotal role in setting realistic schedules and prioritising risk mitigation efforts.

• P50 (The Median):
  • This is the point at which there is a 50% chance that the project will be completed by this date or earlier (In simpler terms, it’s the median of all simulated project completion dates). P50 is often used as the most likely completion date when planning and communicating project timelines.

• P80 (80% Probability):
  • This point indicates there is an 80% chance that the project will be completed by this date or earlier. It represents a higher confidence level than the P50 but is less conservative than the P90 estimate. Essentially, when you look at the P80 completion date, you’re seeing a timeline by which there is a strong likelihood (80% chance) the project will be finished, accounting for the risks and uncertainties identified in the simulation.
• P90 (90% Probability):
  • This point indicates a 90% probability that the project will be completed by this date or earlier. It represents a more conservative estimate, considering a broader range of risks and uncertainties. Project managers might use the P90 to set expectations with stakeholders for a date by which the project is very likely to be completed, incorporating a higher degree of certainty to accommodate for identified risks.

Figure 3: Probability Distribution Graph – Project Finish Date

Practical Example

As per figure 3, the project P50 completion date is on 11/06/2020, a P80 completion date of 15/06/2020, and a P90 completion date of 16/06/2020. The P80 date tells us that, accounting for identified risks, there’s an 80% confidence level the project will complete 15/06/2020.

The wide gap between P50 & P90 of 5 days suggests specific uncertainties and risks that could delay the project. By identifying and addressing the specific risks contributing to this uncertainty, a bid manager can work to narrow the gap, aiming to bring the P90 closer to the P50, thereby increasing confidence in the project’s timely completion.

This helps in setting a realistic yet somewhat optimistic target for the team and stakeholders, providing a clearer picture of the project timeline under the influence of known risks and uncertainties.

Enhancing Project Delivery with SRA

The integration of Schedule Risk Analysis using the Monte Carlo method into project management processes presents a powerful paradigm for navigating project uncertainties. It equips project managers and project teams with a profound understanding of probabilistic outcomes (P50, P80, and P90), enabling them to navigate risks with greater efficacy and confidence.